1. Field of the Invention
The present invention is directed to continuous, real time, high speed, programmable data collection and processing. More particularly, the present invention is directed to a network of intelligent sensor processing modules (SPs) which simultaneously acquire, process and transmit sensor data under the control of a central processor.
2. Discussion of the Related Art
Sensors are used in many environments for many reasons. They can detect noise, vibrations, faults, light, heat, etc. Sensor systems are systems of sensors that receive and forward information. One existing system cables analog outputs to a single location. The sensors are grouped together to form centralized hubs (localizers) which are connected together. This results in long cable runs between the sensors and localizers. In addition, this poses cost installation problems due to the cost of running all the cables from the sensors to the localizers. The system then splits the outputs between an analog summing amplifier and a localizer. The localizer interfaces directly with individual transducers. The localizer includes an analog conditioner which filters and rectifies the sensor outputs. An analog sum is output from each sensor group to an analyzer. The analyzer performs real time detection of transients on coherent sums of each sensor group. Rack and equipment space is required by each of the localizers as well as the central processor. Another problem is electromagnetic interference (EMI) which can contaminate low level sensor signals over the long cable runs.
Another existing system uses a distributed acquisition method for lower bandwidth sampling. The raw individual data samples are serially transmitted. The number of sensors are constrained by the sampling rate and transmission bandwidth. Increasing the sampling rate decreases the number of sensors that can be received over one medium, so potentially a large number of cables might have to be utilized to bring all of the data back to a central location. All of this data is transmitted to a central location where it is to be processed. The central processor must transfer and process large amounts of data. Space must be available to accommodate a large central processing system and the related procurement costs are high.
Neither of the above-mentioned systems, nor any similar systems, reduce cabling, cabling costs or central processor complexity while increasing configuration flexibility, sampling rates, and the number of sensors. Further, none of the systems known in the art provide a network of sensors that simultaneously acquire signals, process commands, process the data into sums and energy footprints, and transmit sensor data under the control of a central processor.